Apparatus and methods to recommend medical information

Abstract

Disclosed and described systems, methods, and apparatus provide facilitate detection, processing, and relevancy analysis of clinical data. An example data event processing system includes a data event processor configured to receive a data event and to trigger, based on receipt of the data event, processing of the data event with respect to a clinical scenario. The example system includes a data relevancy processor configured to process the data event by applying natural language processing and machine learning to the data event based on the clinical scenario and to determine relevancy of the data event with respect to the clinical scenario based on a combination of domain knowledge and user knowledge. The example system includes an interface configured to output the data event and an indication of the relevancy of the data event with respect to the clinical scenario.

What is claimed is: 
     
         1 . A data event processing system comprising:
 a data event processor configured to receive a data event and to trigger, based on receipt of the data event, processing of the data event with respect to a clinical scenario;   a data relevancy processor configured to process the data event by applying natural language processing and machine learning to the data event based on the clinical scenario and to determine relevancy of the data event with respect to the clinical scenario based on a combination of domain knowledge and user knowledge to filter and determine relevancy of the data event with respect to the clinical scenario; and   an interface configured to output the data event and an indication of the relevancy of the data event with respect to the clinical scenario.   
     
     
         2 . The system of  claim 1 , wherein the interface comprises at least one of an application programming interface and a graphical user interface. 
     
     
         3 . The system of  claim 1 , further comprising a data usage monitor configured to monitor usage of data related to the data event. 
     
     
         4 . The system of  claim 1 , wherein the data usage monitor is further configured to receive an input of user preference with respect to data. 
     
     
         5 . The system of  claim 1 , wherein the data relevancy processor applies a relevancy algorithm to the data event to determine relevancy of the data event with respect to the clinical scenario based on a) a similarity score (s index ) for a document associated with the data event and provided as a result of the mining, extraction, and processing of the document and b) a value of a feature (v feat ) from a feature set provided as a result of the mining, extraction, and analysis, where v feat  and s index , are used to calculate a relevancy score for the data event with respect to the clinical scenario according to:
   Relevancy= f ( s   index   ,v   feat ).   
     
     
         6 . The system of  claim 1 , wherein the indication of relevancy is a factor in selecting the data event for viewing in comparison with data from the clinical scenario. 
     
     
         7 . The system of  claim 1 , wherein the indication of relevancy comprises a relevancy score. 
     
     
         8 . A computer-readable storage medium including program instructions for execution by a computing device, the instructions, when executed, causing the computing device to implement a data event processing system, the system comprising:
 a data event processor configured to receive a data event and to trigger, based on receipt of the data event, processing of the data event with respect to a clinical scenario;   a data relevancy processor configured to process the data event by applying natural language processing and machine learning to the data event based on the clinical scenario and to determine relevancy of the data event with respect to the clinical scenario based on a combination of domain knowledge and user knowledge to filter and determine relevancy of the data event with respect to the clinical scenario; and   an interface configured to output the data event and an indication of the relevancy of the data event with respect to the clinical scenario.   
     
     
         9 . The computer-readable storage medium of  claim 8 , wherein the interface comprises at least one of an application programming interface and a graphical user interface. 
     
     
         10 . The computer-readable storage medium of  claim 8 , wherein the system further comprises a data usage monitor configured to monitor usage of data related to the data event. 
     
     
         11 . The computer-readable storage medium of  claim 8 , wherein the data usage monitor is further configured to receive an input of user preference with respect to data. 
     
     
         12 . The computer-readable storage medium of  claim 8 , wherein the data relevancy processor applies a relevancy algorithm to the data event to determine relevancy of the data event with respect to the clinical scenario based on a) a similarity score (s index ) for a document associated with the data event and provided as a result of the mining, extraction, and processing of the document and b) a value of a feature (v feat ) from a feature set provided as a result of the mining, extraction, and analysis, where v feat  and s index , are used to calculate a relevancy score for the data event with respect to the clinical scenario according to:
   Relevancy= f ( s   index   ,v   feat ).   
     
     
         13 . The computer-readable storage medium of  claim 8 , wherein the indication of relevancy is a factor in selecting the data event for viewing in comparison with data from the clinical scenario. 
     
     
         14 . The computer-readable storage medium of  claim 8 , wherein the indication of relevancy comprises a relevancy score. 
     
     
         15 . A method of medical information identification and relevancy determination, the method comprising:
 triggering, automatically using a processor based on receipt of a data event, processing of the data event with respect to a clinical scenario;   processing the data event, using the processor, by applying natural language processing and machine learning to the data event based on the clinical scenario;   determining, using the processor, relevancy of the data event with respect to the clinical scenario based on a combination of domain knowledge and user knowledge to filter and determine relevancy of the data event with respect to the clinical scenario; and   outputting the data event and an indication of the relevancy of the data event with respect to the clinical scenario.   
     
     
         16 . The method of  claim 15 , wherein outputting comprises outputting via at least one of an application programming interface and a graphical user interface. 
     
     
         17 . The method of  claim 15 , further comprising monitoring, using the processor, usage of data related to the data event. 
     
     
         18 . The method of  claim 15 , further comprising receiving an input of user preference with respect to data and incorporating the user preference into determining relevancy of the data event. 
     
     
         19 . The method of  claim 15 , wherein determining relevancy of the data event comprises applying a relevancy algorithm to the data event to determine relevancy of the data event with respect to the clinical scenario based on a) a similarity score (s index ) for a document associated with the data event and provided as a result of the mining, extraction, and processing of the document and b) a value of a feature (v feat ) from a feature set provided as a result of the mining, extraction, and analysis, where v feat  and s index , are used to calculate a relevancy score for the data event with respect to the clinical scenario according to:
   Relevancy= f ( s   index   ,v   feat ).   
     
     
         20 . The method of  claim 15 , further comprising selecting, based on the indication of relevancy, the data event for viewing in comparison with data from the clinical scenario.